Effect of Ambient Voice Technology, Natural Language Processing, and Artificial Intelligence on the Patient–Physician Relationship

Abstract

Abstract Background The method of documentation during a clinical encounter may affect the patient–physician relationship. Objectives Evaluate how the use of ambient voice recognition, coupled with natural language processing and artificial intelligence (DAX), affects the patient–physician relationship. Methods This was a prospective observational study with a primary aim of evaluating any difference in patient satisfaction on the Patient–Doctor Relationship Questionnaire-9 (PDRQ-9) scale between primary care encounters in which DAX was utilized for documentation as compared to another method. A single-arm open-label phase was also performed to query direct feedback from patients. Results A total of 288 patients were include in the open-label arm and 304 patients were included in the masked phase of the study comparing encounters with and without DAX use. In the open-label phase, patients strongly agreed that the provider was more focused on them, spent less time typing, and made the encounter feel more personable. In the masked phase of the study, no difference was seen in the total PDRQ-9 score between patients whose encounters used DAX (median: 45, interquartile range [IQR]: 8) and those who did not (median: 45 [IQR: 3.5]; p = 0.31). The adjusted odds ratio for DAX use was 0.8 (95% confidence interval: 0.48–1.34) for the patient reporting complete satisfaction on how well their clinician listened to them during their encounter. Conclusion Patients strongly agreed with the use of ambient voice recognition, coupled with natural language processing and artificial intelligence (DAX) for documentation in primary care. However, no difference was detected in the patient–physician relationship on the PDRQ-9 scale.